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Record W2534669981 · doi:10.1109/bmse.2012.6466175

Measurement of rolling shear modulus of Cross Laminated Timber: Exploratory study using downscaled specimens under variable span bending tests

2012· article· en· W2534669981 on OpenAlexaff
Qinyi Zhou, Meng Gong, Ying Hei Chui, Mohammand Mohammand

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsFPInnovationsUniversity of New Brunswick
Fundersnot available
KeywordsShear modulusShear (geology)Composite materialStructural engineeringMaterials scienceYoung's modulusSpan (engineering)MathematicsEngineering

Abstract

fetched live from OpenAlex

The purpose of this study was to measure the rolling shear modulus of Cross Laminated Timber (CLT), which was achieved by conducting 3-point bending tests with variable span using downscaled sandwich specimens. Two types of sandwich specimens were employed: steel-wood-steel (SWS) and wood-wood-wood (WWW). Experimental results from SWS specimens were verified with those predicted from WWW ones through the shear analogy method. Effects of span-to-depth ratio (l/h) and growth ring orientation on rolling shear modulus (GRT) were also examined. It was found that the average deflection of WWW specimens tested at l/h of 6.5 could be well predicted using the shear analogy method based on true elasticity of modulus (Em) and GRTof the cross layer measured using SWS specimens under variable span tests. The results also showed that the cross layer of `in-between' growth ring orientation could gain the higher rolling shear modulus than that of flat sawn or quarter sawn one.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.265
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2012
Admission routes1
Has abstractyes

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